Most of interpretable models are based on hand-crafted energy potentials that
require some domain expertise. Helbing and Molnar [1]} have
highly impacted the field by introducing a pedestrian motion model based on
attractive and repulsive forces referred to as the Social Force model.
This has been shown to achieve competitive results even on modern pedestrian
datasets [2]}, [3]}. This method was used
extensively to study panic behavior in dense
crowds [4]}, [5]}, [6]},
applied in robotics [7]} and activity
understanding [8]}, [9]}, [10]}, [11]}, [12]}, [13]}, [14]}.
Variants of the model have been proposed by extending it to a multi-class
case [15]} or by including rotational
inertia [16]}. Using a dataset of dense crowds,
Seer [17]} have calibrated the Social Force parameters to
produce a model with better predictive power.
Recently, Chen [18]} presented a nice review on all extensions of the Social Force model.
